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Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital?
OBJECTIVE: Older patients who are at risk of poor healthcare outcomes should be recognised early during hospital admission to allow appropriate interventions. It is unclear whether routinely collected data can identify high-risk patients. The aim of this study was to define current practice with reg...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553791/ https://www.ncbi.nlm.nih.gov/pubmed/28797300 http://dx.doi.org/10.1186/s13104-017-2705-7 |
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author | Ibrahim, Kinda Owen, Charlotte Patel, Harnish P. May, Carl Baxter, Mark Sayer, Avan A. Roberts, Helen C. |
author_facet | Ibrahim, Kinda Owen, Charlotte Patel, Harnish P. May, Carl Baxter, Mark Sayer, Avan A. Roberts, Helen C. |
author_sort | Ibrahim, Kinda |
collection | PubMed |
description | OBJECTIVE: Older patients who are at risk of poor healthcare outcomes should be recognised early during hospital admission to allow appropriate interventions. It is unclear whether routinely collected data can identify high-risk patients. The aim of this study was to define current practice with regard to the identification of older patients at high risk of poor healthcare outcomes on admission to hospital. RESULTS: Interviews/focus groups were conducted to establish the views of 22 healthcare staff across five acute medicine for older people wards in one hospital including seven nurses, four dieticians, seven doctors, and four therapists. In addition, a random sample of 60 patients’ clinical records were reviewed to characterise the older patients, identify risk assessments performed routinely on admission, and describe usual care. We found that staff relied on their clinical judgment to identify high risk patients which was influenced by a number of factors such as reasons for admission, staff familiarity with patients, patients’ general condition, visible frailty, and patients’ ability to manage at home. “Therapy assessment” and patients’ engagement with therapy were also reported to be important in recognising high-risk patients. However, staff recognised that making clinical judgments was often difficult and that it might occur several days after admission potentially delaying specific interventions. Routine risk assessments carried out on admission to identify single healthcare needs included risk of malnutrition (completed for 85% patients), falls risk (95%), moving and handling assessments (85%), and pressure ulcer risk assessments (88%). These were not used collectively to highlight patients at risk of poor healthcare outcomes. Thus, patients at risk of poor healthcare outcomes were not explicitly identified on admission using routinely collected data. There is a need for an early identification of these patients using a valid measure alongside staff clinical judgment to allow timely interventions to improve healthcare outcomes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-017-2705-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5553791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-55537912017-08-15 Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? Ibrahim, Kinda Owen, Charlotte Patel, Harnish P. May, Carl Baxter, Mark Sayer, Avan A. Roberts, Helen C. BMC Res Notes Research Note OBJECTIVE: Older patients who are at risk of poor healthcare outcomes should be recognised early during hospital admission to allow appropriate interventions. It is unclear whether routinely collected data can identify high-risk patients. The aim of this study was to define current practice with regard to the identification of older patients at high risk of poor healthcare outcomes on admission to hospital. RESULTS: Interviews/focus groups were conducted to establish the views of 22 healthcare staff across five acute medicine for older people wards in one hospital including seven nurses, four dieticians, seven doctors, and four therapists. In addition, a random sample of 60 patients’ clinical records were reviewed to characterise the older patients, identify risk assessments performed routinely on admission, and describe usual care. We found that staff relied on their clinical judgment to identify high risk patients which was influenced by a number of factors such as reasons for admission, staff familiarity with patients, patients’ general condition, visible frailty, and patients’ ability to manage at home. “Therapy assessment” and patients’ engagement with therapy were also reported to be important in recognising high-risk patients. However, staff recognised that making clinical judgments was often difficult and that it might occur several days after admission potentially delaying specific interventions. Routine risk assessments carried out on admission to identify single healthcare needs included risk of malnutrition (completed for 85% patients), falls risk (95%), moving and handling assessments (85%), and pressure ulcer risk assessments (88%). These were not used collectively to highlight patients at risk of poor healthcare outcomes. Thus, patients at risk of poor healthcare outcomes were not explicitly identified on admission using routinely collected data. There is a need for an early identification of these patients using a valid measure alongside staff clinical judgment to allow timely interventions to improve healthcare outcomes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-017-2705-7) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-10 /pmc/articles/PMC5553791/ /pubmed/28797300 http://dx.doi.org/10.1186/s13104-017-2705-7 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Note Ibrahim, Kinda Owen, Charlotte Patel, Harnish P. May, Carl Baxter, Mark Sayer, Avan A. Roberts, Helen C. Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title | Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title_full | Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title_fullStr | Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title_full_unstemmed | Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title_short | Can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
title_sort | can routine clinical data identify older patients at risk of poor healthcare outcomes on admission to hospital? |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5553791/ https://www.ncbi.nlm.nih.gov/pubmed/28797300 http://dx.doi.org/10.1186/s13104-017-2705-7 |
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